The New Age of Data Science: in conversation with Aaron Goldman, CMO at 4C

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Watch Aaron Goldman, CMO, 4C talk about using data science to plan, buy and measure media at scale. He suggests that marketers and advertisers adapt to the new era of self-serve programmatic ad buying as it offer a competitive advantage. Goldman has been running the digital marketing rap game for more than 15 years. When he’s not busy Googling himself, Goldman is running around Chicago with his wife, Lisa, daughter, Eliara, and twins, Ethan and Mila.

You are bringing data science to the traditional media planning and buying function. How different does this function (of media planning, buying and selling) look post the introduction of data science to drive decision making?

we can use data science to plan, buy, and measure media at scale and get better return on investment.

Your data science techniques claim to help better understand consumer behaviour and create ‘affinities’ so brands can better choose cross-channel advertising opportunities. What are these ‘affinities’ and how does it help targeting?

Affinities are audience behaviours that help us understand if people are more or less likely to be interested in a certain brand or product. For example, people who engage with Star Wars on social media are 8 times more likely to engage with IBM and 6 times more likely to engage with LEGO. These are important brand insights to consider when planning marketing promotions, ad targeting, and creative strategies.

We also go beyond social and bring in TV data and offline purchase behavior to build a complete picture of audience personas as part of the 4C Insights Affinity Graph™.

What are the biggest challenges that B2Bs face while planning and buying media in the omni-channel world? How do you think data science can help mitigate risk and optimize marketing for these B2Bs?

Data science is great and can help us identify and reach our most valuable audiences. But with great data science comes great responsibility. As Account Based Marketing (ABM) becomes the killer B2B strategy, we have to resist the urge to tell people how much we know about them when targeting ads or other messages. Instead,

we should use the insights to draw them in on their terms, during their normal day-to-day, with well-timed messaging.

Tell us more about self-serve programmatic ad buying and how it offers advertisers a competitive advantage? How is 4C powering self-serve programmatic ad planning & buying?

Programmatic ad buying used to mean writing a check to a company that would handle all your targeting, bidding, ad delivery, and measurement. You just told them what you goal was, and they’d do the rest. Sometimes they did it program-manually with people pulling levers on top of machines. And sometimes it was truly automated with technology. But in all cases, it was done opaquely so that the advertiser did not have transparency into what variables were being deployed and where exactly the ads were actually running.

With self-serve programmatic platforms, you can keep total control over what you’re buying and have total visibility into where you’re running and why.

What about measuring the cross-channel impact of content? For example, ads on TV have a measurable impact on social media engagement, but how would data science help measure and create intel out of that? Could you give us an example?

We use our data science to measure when and where a TV ad was delivered and if it drove engagement on social media. We look at the two minutes before and after the commercial ran to see if there was a lift in activity on social. We can also go one step further and synchronize ads across screens so that when the Star Wars trailer runs on TV we can pop up an ad on Instagram or Snapchat with local theatres or showtimes.

We’d like to hear your story of how you (Aaron) got into data science. What motivated you to work in data science? What advice would you give to people aspiring to a career in Data Science?

I backdoored my way into data science. My major in school was advertising and when I graduated I got a job at an one of the first online ad networks. I knew digital was the future but didn’t realize how data-driven it was.

Over time, with more and more data being applied to digital marketing it was clear the winner would be whoever had the biggest data sets and, more importantly, the ability to mine signal from noise within them.

That’s what drew me to data science and eventually to 4C.

For anyone looking to get into this field I’d tell them to sharpen their analytical skills any way they can – from learning how to use business intelligence tools to just generally being able to think critically and challenge assumptions.

When it comes to the latter, books like Freakonomics are a great place to start. And then there’s one I wrote ago called Everything I Know About Marketing I Learned from Google. It’s 7 years old at this point so a lot has changed but the lessons are really timeless.

Let’s wrap with a look forward. What’s coming up that you’re excited about in two areas: in the Adtech or social media market in general—perhaps a trend or tool; and within 4C—any new features or upcoming upgrades?

From an industry perspective, I’m really excited about GDPR (General Data Protection Regulation) and other forms of legislation that will reign in the use of data for digital marketing. Just kidding – that’s what I’m least excited about! I’m all for self-regulation and think the various trade associations we have and initiatives like ads.txt are great ways to keep all players aligned on the pitch.